४ थी गणित हिंदी
| Publication Language |
Hindi |
|---|---|
| License Type |
Open Access |
| Publication Type |
Textbooks |
| Publication Author |
Balbharati |
| Publisher |
Balbharati |
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Euler?s Number. Why Is Eule’s Number “E” the Basis of Natural Logarithm Functions
Document from the year 2016 in the subject Mathematics - Miscellaneous, grade: A, , course: IB Math HL, language: English, abstract: When the concept of logarithms was first introduced to me, a plethora of questions revolved around my mind. My inquisitiveness compelled me to think and ask questions as to where are the practical applications of logarithms, why do we take different bases of these functions and what is the need for natural logarithms. Amongst these questions, one particularly intrigued me: why is e particularly the base of the natural logarithm. Why out of all numbers that exist did we choose e as the base of the natural logarithm function? I was fascinated by why taking the base e made the normal logarithm a natural logarithm. Therefore, to quench the curiosity of many others like me, I will show through this paper that why e is the correct choice for the base of exponential and natural logarithm functions. I shall also be exploring the most important property of e, via this paper.
Statistical Tools for Measuring Agreement
Agreement assessment techniques are widely used in examining the acceptability of a new or generic process, methodology and/or formulation in areas of lab performance, instrument/assay validation or method comparisons, statistical process control, goodness-of-fit, and individual bioequivalence. Successful applications in these situations require a sound understanding of both the underlying theory and methodological advances in handling real-life problems. This book seeks to effectively blend theory and applications while presenting readers with many practical examples. For instance, in the medical device environment, it is important to know if the newly established lab can reproduce the instrument/assay results from the established but outdating lab. When there is a disagreement, it is important to differentiate the sources of disagreement. In addition to agreement coefficients, accuracy and precision coefficients are introduced and utilized to characterize these sources. This book will appeal to a broad range of statisticians, researchers, practitioners and students, in areas of biomedical devices, psychology, medical research, and others, in which agreement assessment are needed. Many practical illustrative examples will be presented throughout the book in a wide variety of situations for continuous and categorical data.